# Program

An overview of the structure of the program is given below.

Except for the first plenary talk, all the remaining plenary talks, lectures and poster sessions will be held at the Digital Technology Center of the University of Minnesota, which is located at the 4th and 5th floors of the Walter Library. The first plenary talk (Wednesday 1:20 to 2:20) will be held at Keller Hall.

All the meals shown in the program above will be provided by the conference.

## Detailed Program

### **Wednesday**

**Wednesday**

#### 1:20pm-2:20pm: Plenary - Jennifer Neville

Towards Relational AI - the good, the bad, and the ugly of learning over networks

#### 2:20pm-2:50pm: Transition between Keller Hall and Walter Library

#### 2:50pm-3:30pm: Lecture - Spectral Methods

"Lifting Structures in the Spectral Domain for Graph Filter Banks", David Tay and Antonio Ortega.

"Online Graph Spectra Learning", Stefan Dernbach and Don Towsley.

#### 3:30pm-4:00pm: Coffee break

#### 4:00pm-6:00pm: Poster Session

"Network Constraints Against Cyber attacks in Power Systems", Gal Morgenstern and Tirza Routtenberg.

"Graph Blind Source Separation with Applications for Power Systems", Sivan Grotas and Tirza Routtenberg.

"What's in a Frequency: New tools for graph Fourier Transform visualization", Benjamin Girault and Antonio Ortega.

"Controllability of Bandlimited Graph Processes over Random Time-Varying Graphs", Fernando Gama, Elvin Isufi, Alejandro Ribeiro and Geert Leus.

"Graph Signal Analytics for Liver Quality Assessment based on Thermal Images", Sahand Hajifar and Hongyue Sun.

"Digraph Fourier Transform: Sparse Signal-adapted Representations and Distributed Filtering", Rasoul Shafipour and Gonzalo Mateos.

"Personalized Diffutions for Recommendation", Athanasios N. Nikolakopoulos, Dimitris Berberidis, George Karypis and Georgios B Giannakis.

"Deep Graph Topology Learning for 3D Point Cloud Reconstruction", Chaojing Duan, Siheng Chen, Dong Tian, José Moura and Jelena Kovacevic.

"Proximal Newton Method with Novel Line Search for Sparse Gaussian Graphical Model Inference", Tianyi Liu, Minh Hoang Trinh, Yang Yang and Marius Pesavento.

"Estimating Network Processes via Blind Identification of Multiple Graph Filters", Yu Zhu, Fernando Iglesias, Antonio Marques and Santiago Segarra.

"Quantifying the Spread of a Graph Signal", Antoine Mazarguil and Laurent Oudre.

"Iterative Algorithms for Inverse Filtering on Spatially Distributed Networks", Nazar Emirov.

"Spectral bounds of the regularized normalized Laplacian for random geometric graphs", Mounia Hamidouche, Laura Cottatellucci and Konstantin Avratchenkov.

"Graph Filtering of Time-Varying Signals over Random Asymmetric Wireless Sensor Networks", Leila Ben Saad and Baltasar Beferull-Lozano.

#### 6:00pm-7:00pm: Welcome drink

### **Thursday**

**Thursday**

#### 8:30am-9:30am: Plenary - Naoki Saito

The First Steps toward Building Natural Graph Wavelets

#### 9:30am-10:00am: Coffee break

#### 10:00am-12:00pm: Lecture - Sampling & Reconstruction

"Fast Graph Sampling using Gershgorin Disc Alignment", Yuanchao Bai, Gene Cheung, Fen Wang, Xianming Liu and Wen Gao.

"Generalized Sampling on Graphs With A Subspace Prior", Yuichi Tanaka and Yonina Eldar.

"Blue-Noise Sampling on Graphs", Alejandro Parada-Mayorga, Daniel Lau, Jhony Giraldo and Gonzalo Arce.

"Matrix completion and extrapolation via kernel regression", Pere Giménez-Febrer, Alba Pagès-Zamora and Georgios B. Giannakis.

"Spectral Partitioning of Time-Varying Networks from Nodal Observations", Michael Schaub, Santiago Segarra and Hoi-To Wai.

"Discovering adversaries over large-scale graphs", Vassilis N. Ioannidis, Dimitris K. Berberidis and Georgios B. Giannakis.

#### 12:00pm-1:20pm: Lunch

#### 1:20pm-2:20pm: Plenary - Gonzalo Mateos

Digraph Signal Processing: Orthonormal Transforms and Network Inference

#### 2:30pm-3:30pm: Lecture - Graph Neural Networks

"Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs", Elvin Isufi, Fernando Gama and Alejandro Ribeiro.

"A Unified Deep Learning Formalism for Processing Graph Signals", Myriam Bontonou, Carlos Eduardo Rosar Kos Lassance, Jean-Charles Vialatte and Vincent Gripon.

"Pooling in Graph Convolutional Neural Networks", Mark Cheung, John Shi, Oren Wright, Yao Jiang and José Moura.

#### 3:30pm-4:00pm: Coffee break

#### 4:00pm-6:00pm: Poster Session

"Introducing Graph Smoothness Loss for Training Deep Learning Architectures", Myriam Bontonou, Carlos Eduardo Rosar Kos Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang and Antonio Ortega.

"Gated Graph Convolutional Recurrent Neural Networks", Luana Ruiz, Fernando Gama and Alejandro Ribeiro.

"Large Scale Wireless Power Allocation with Graph Neural Networks", Mark Eisen and Alejandro Ribeiro.

"Stability Properties of Graph Convolutional Neural Networks", Fernando Gama, Joan Bruna and Alejandro Ribeiro.

"Bounding Indicator Function Smoothness for Neural Networks Robustness", Carlos Eduardo Rosar Kos Lassance, Vincent Gripon and Antonio Ortega.

"Deep Power-Flow Neural Network Driven By Physics Guided Theory and Topology", Xinyue Hu, Saurabh Verma and Zhi-Li Zhang.

"A Recurrent Graph Neural Network for Multi-relational Data", Vassilis N. Ioannidis, Antonio G. Marques and Georgios B. Giannakis.

"Variational Node Embedding", Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna Narayanan, Nick Duffield, Mingyuan Zhou and Xiaoning Qian.

"Permutation Invariant Representations for Graph Convolutional Neural Networks", Naveed Haghani and Radu Balan.

"Geometric Scattering for Graph Data Analysis", Feng Gao, Guy Wolf and Matthew Hirn.

"Graph Convolutional Neural Networks via Scattering,” Dongmian Zou and Gilad Lerman.

#### 7:15pm-9:30pm: Gala dinner at "Fogo de Chao"

### **Friday**

**Friday**

#### 8:30am-9:30am: Plenary - Gal Mishne

Graph Signal Processing on Tensors

#### 9:30am-10:00am: Coffee break

#### 10:00am-12:00pm: Lecture - Applications

"Atrial Activity Extraction Based on Graph-Time Signal Processing", Miao Sun, Elvin Isufi, Natasja de Groot and Richard Hendriks.

"Large-Scale 3D Point Cloud Representations via Graph Inception Networks with Applications to Autonomous Driving", Siheng Chen.

"Applying Graph Signal Processing to Direction-of-Arrival Estimation", Eldridge Alcantara, Les Atlas and Shima Abadi.

"Semi-Supervised Classification via Alternating Binary Classifier and Graph Learning", Cheng Yang, Gene Cheung and Vladimir Stankovic.

"Estimating Brain Connectomes from Multimodal Data", Claire Donnat and Susan Holmes.

"Enhancing experimental signals in single-cell RNA-sequencing data using graph signal processing", Daniel Burkhardt, Jay Stanley, Guy Wolf, David van Dijk and Smita Krishnaswamy.

#### 12:00pm-1:20pm: Lunch

#### 1:20pm-2:20pm: Plenary - Alejandro Ribeiro

Graph Neural Networks

#### 2:30pm-3:30pm: Lecture - Graph Topology ID

"Time-Varying Graph Inference with Sparseness Constraint on Temporal Variation", Koki Yamada, Yuichi Tanaka and Antonio Ortega.

"Network Reconstruction from Graph-Stationary Signals with Hidden Nodal Variables", Andrei Buciulea, Cristobal Cabrera and Antonio Marques.

"Online Topology Identification from Vector Autoregressive Time Series", Bakht Zaman, Luis Miguel Lopez Ramos, Daniel Romero and Baltasar Beferull-Lozano.

#### 3:30pm-4:00pm: Coffee break

#### 4:00pm-5:40pm: Lecture - Filtering

"Trend Filtering of Vector-Valued Graph Signals", Harlin Lee, Rohan Varma, Yuejie Chi and Jelena Kovacevic.

"Efficient Graph Filter for Large-Scale Point Clouds", Rui Liu, Antonio Ortega, Ngai-Man Cheung and Yuren Zhou.

"Spectrum-Adapted Polynomial Approximation for Matrix Functions", Li Fan, David Shuman, Shashanka Ubaru and Yousef Saad.

"State-Space Based Network Topology Identification", Mario Coutino and Geert Leus.

"Cascaded Graph Filters for Distributed Consensus", Geert Leus and Mario Coutino.